import matplotlib
matplotlib.use('Agg')
from pylab import *
import JSAnimation_frametools as J
plotdir = '_plots' # to store png files for each figure
J.make_plotdir(plotdir, clobber=True) # ok to clobber if it already exists
input_data = loadtxt('input_data.txt')
n = int(input_data[0])
nterms = int(input_data[1])
x, f = loadtxt('xf.txt', unpack=True)
data = loadtxt('frames.txt')
terms = reshape(data[:,0], (n+2, nterms), order='F')
fsums = reshape(data[:,1], (n+2, nterms), order='F')
for k in range(nterms):
term = terms[:,k]
fsum = fsums[:,k]
clf()
subplot(2,1,1)
plot(x,fsum,'b-')
plot(x,f,'r-')
title('Sum of first %s terms in Fourier series' % (k+1))
axis([0,pi,-1.0,30.0])
import matplotlib
matplotlib.use('Agg') # graphics backend for hardcopy
from pylab import *
from JSAnimation import IPython_display
import JSAnimation_frametools as J
plotdir = '_plots' # to store png files for each figure
J.make_plotdir(plotdir, clobber=True) # ok to clobber if it already exists
x = linspace(0., 10., 1001)
nsteps = 21
dt = 11. / (nsteps + 1)
plotdir = '_plots'
for n in range(nsteps + 1):
t = n * dt
x0 = x - 1. - t
u = sin(20. * x0) * exp(-5. * x0**2)
clf()
plot(x, u, 'b')
ylim(-1.2, 1.2)
title('Wave packet at t = %8.4f' % t, fontsize=20)
# Save this frame:
J.save_frame(n, plotdir, verbose=False)
#show()
anim = J.make_anim(plotdir)
import matplotlib
matplotlib.use('Agg')
from matplotlib import image, animation
from matplotlib import pyplot as plt
import JSAnimation_frametools as J
from JSAnimation import IPython_display
import numpy as np
import glob
plotdir = '_plots'
J.make_plotdir(plotdir, clobber='true')
fid = open('input_data.txt')
n = int(fid.readline())
tfinal = float(fid.readline())
fid.readline()
nsteps = int(fid.readline())
ax = plt.axes(xlim=(0, np.pi), ylim=(-1, 1))
line, = ax.plot([], [], lw=2)
line.set_data(range(n), range(n))
data = open('solution.txt')
for i in range(nsteps + 1):
soln = []
plt.clf()
for j in range(n + 2):
soln.append(float(data.readline()))
plt.axes(xlim=(0, np.pi), ylim=(-1, 1))
plt.plot(np.arange(0, np.pi, np.pi / (n + 2)), soln)
plt.plot(np.arange(0, np.pi, np.pi / (n + 2)), soln, 'bo')
t = "%.3f" % (i * tfinal / nsteps)